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[2023-10-23 04:42:02,107::train::INFO] [train] Iter 566386 | loss 0.3876 | loss(rot) 0.3551 | loss(pos) 0.0325 | loss(seq) 0.0000 | grad 8.0747 | lr 0.0000 | time_forward 2.9270 | time_backward 3.8370 |
[2023-10-23 04:42:04,772::train::INFO] [train] Iter 566387 | loss 0.5072 | loss(rot) 0.4784 | loss(pos) 0.0204 | loss(seq) 0.0084 | grad 66.4744 | lr 0.0000 | time_forward 1.2630 | time_backward 1.3990 |
[2023-10-23 04:42:11,830::train::INFO] [train] Iter 566388 | loss 0.4634 | loss(rot) 0.3525 | loss(pos) 0.0119 | loss(seq) 0.0991 | grad 8.8824 | lr 0.0000 | time_forward 3.0530 | time_backward 4.0020 |
[2023-10-23 04:42:14,065::train::INFO] [train] Iter 566389 | loss 0.4040 | loss(rot) 0.2054 | loss(pos) 0.0556 | loss(seq) 0.1430 | grad 2.7114 | lr 0.0000 | time_forward 1.0300 | time_backward 1.2010 |
[2023-10-23 04:42:16,768::train::INFO] [train] Iter 566390 | loss 0.9848 | loss(rot) 0.9510 | loss(pos) 0.0286 | loss(seq) 0.0052 | grad 5.0795 | lr 0.0000 | time_forward 1.2990 | time_backward 1.3900 |
[2023-10-23 04:42:23,832::train::INFO] [train] Iter 566391 | loss 1.2717 | loss(rot) 1.0771 | loss(pos) 0.0402 | loss(seq) 0.1543 | grad 4.2980 | lr 0.0000 | time_forward 3.0320 | time_backward 4.0290 |
[2023-10-23 04:42:26,545::train::INFO] [train] Iter 566392 | loss 0.2916 | loss(rot) 0.0320 | loss(pos) 0.0735 | loss(seq) 0.1862 | grad 3.1005 | lr 0.0000 | time_forward 1.2860 | time_backward 1.4250 |
[2023-10-23 04:42:33,608::train::INFO] [train] Iter 566393 | loss 0.3811 | loss(rot) 0.2235 | loss(pos) 0.0126 | loss(seq) 0.1450 | grad 2.1247 | lr 0.0000 | time_forward 3.0650 | time_backward 3.9940 |
[2023-10-23 04:42:40,136::train::INFO] [train] Iter 566394 | loss 1.8645 | loss(rot) 1.8135 | loss(pos) 0.0451 | loss(seq) 0.0059 | grad 4.2737 | lr 0.0000 | time_forward 2.8250 | time_backward 3.7000 |
[2023-10-23 04:42:43,156::train::INFO] [train] Iter 566395 | loss 1.4804 | loss(rot) 1.1390 | loss(pos) 0.0459 | loss(seq) 0.2956 | grad 9.4314 | lr 0.0000 | time_forward 1.3690 | time_backward 1.6480 |
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